Abstract

In content-based Image Retrieval (CBIR) application, a large amount of data is processed. Among various low-level features like color, shape and texture, color is an important feature and represented in the form of histogram. It is essential that features required to be coded in such a way that the storage space requirement is low and processing speed is high. In this paper, we propose a method for indexing of images in the large database with lossy compression technique known as Block Truncation Coding (BTC) along with two different color feature extraction methods - Color Moment and Color Auto-correlogram. Block truncation coding divided the original image into multiple non-overlapping blocks and then retrieve the required features. The proposed method performs better.

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